Humboldt-Universität zu Berlin - Faculty of Mathematics and Natural Sciences - Process Management and Information Systems

OLD TOPICS

 
Topic 1: Visual Concepts for Depicting Varying Activity Behaviors (B. Informatik/KombiB. Lehramt/ M. Information Systems)
 
Description: Process models treat all activities as "equal," even when they behave very differently in real life. Failing to address this can result in complex and misleading visualizations. For this topic, we define and identify varying activity behaviors in event logs and design a set of concepts to visualize them properly. We demonstrate the effectiveness of these designs in a user study.
 
Initial References:
[1] D. Moody, “The ‘Physics’ of Notations: Toward a Scientific Basis for Constructing Visual Notations in Software Engineering,” *IEEE Transactions on Software Engineering*, vol. 35, no. 6, pp. 756–779, Dec. 2009, doi: https://doi.org/10.1109/TSE.2009.67.
[2] A. Pini, R. Brown, and M. T. Wynn, “Process Visualization Techniques for Multi-perspective Process Comparisons,” in *Asia Pacific Business Process Management - Third Asia Pacific Conference, AP-BPM 2015, Busan, South Korea, June 24-26, 2015, Proceedings*, 2015, pp. 183–197. doi: https://doi.org/10.1007/978-3-319-19509-4_14.
 

Supervisor: Christoffer Rubensson

 

 

Topic 2: Visual Strategies for Handling Large Event Networks  (M. Informatik/ M. Information Systems)
 
Description: Event data can be visualized as a directed graph along a two-dimensional Cartesian coordinate system depicting execution time and type. Such graphs provide visual structure and essential performance-related cues but can be ineffective for larger datasets of event data. For this topic, we define a set of techniques for handling large event networks based on common layout strategies. We implement the techniques as a prototype and test their effectiveness in either a computational experiment or a user study.
 
Initial References:
[1] S. G. Eick and A. F. Karr, “Visual Scalability,” *Journal of Computational and Graphical Statistics*, vol. 11, no. 1, pp. 22–43, 2002, URL: http://www.jstor.org/stable/1391126.
[2] F. Du, B. Shneiderman, C. Plaisant, S. Malik, and A. Perer, “Coping with Volume and Variety in Temporal Event Sequences: Strategies for Sharpening Analytic Focus,” *IEEE Transactions on Visualization and Computer Graphics*, vol. 23, no. 6, pp. 1636–1649, Jun. 2017, doi: https://doi.org/10.1109/TVCG.2016.2539960.
[3] S. Esser and D. Fahland, “Multi-Dimensional Event Data in Graph Databases,” *Journal on Data Semantics*, vol. 10, no. 1, pp. 109–141, Jun. 2021, doi: https://doi.org/10.1007/s13740-021-00122-1.
 
Supervisor: Christoffer Rubensson
 
 

Topic 3: Title: Assessing the risk of quantum computers in detail using a risk assessment framework (Bachelor/Master)

 

Description: Since quantum computers will be able to decrypt currently used asymmetric cryptography, companies need to take action in order to keep their cryptography safe. One solution to be safe against quantum computer attacks is to migrate to post-quantum cryptography (PQC). But before initiating such a migration, it is essential to conduct a structured risk assessment to evaluate the relevance and urgency of the threat. This thesis aims to systematically identify, analyze, and evaluate the risks associated with quantum computing by applying a recognized information security risk management framework.

 

Initial References:

[1] Chinelo, A. F. (2025). Quantum Computing and Its Implications for Cryptographic Security. The International Journal of Business Management and Technology, 9(2). https://www.theijbmt.com/archive/0962/1829026576.pdf

[2] Scholten, T. L., Williams, C. J., Moody, D., Mosca, M., Hurley, W., Zeng, W. J., Troyer, M., & Gambetta, J. M. (2024). Assessing the Benefits and Risks of Quantum Computers (No. arXiv:2401.16317). arXiv. https://doi.org/10.48550/arXiv.2401.16317

[3] Näther, C., Herzinger, D., Gazdag, S.-L., Steghöfer, J.-P., Daum, S., & Loebenberger, D. (2024). Migrating Software Systems Toward Post-Quantum Cryptography-A Systematic Literature Review. IEEE Access, 12, 132107–132126. https://doi.org/10.1109/ACCESS.2024.3450306

 

Supervisor: Jennifer Brettschneider

 

 

Topic 4: Enhancing Event Logs from German State Parliaments via Feature Engineering for Improved Comparative Analysis (Bachelor/Master)

 

Description: Context plays a crucial role for meaningful process analysis and fair comparisons. To include contextual information in data sets, feature engineering techniques can be used. This thesis focuses on a recently generated data set capturing the executions of processes in German state parliaments. Using feature engineering techniques, the data set will be enhanced with context information. For instance, information about the political parties and their opinions on important topics could be considered (e.g., from the Wahl-O-Mat) and the complexity and controversiality of law proposals could be assessed (e.g., using LLMs). Naively, the idea behind this is that legislative processes may prove to be more feasible and quicker if the political parties have more in common or if a law proposal is less complex or not controversial.

 

Initial References:

 

[1] Franzoi, S., Hartl, S., Grisold, T. et al. Explaining process dynamics: a Process Mining Context Taxonomy for sense-making. Process Sci 2, 2 (2025). https://doi.org/10.1007/s44311-025-00008-6

[2] Verdonck, T., Baesens, B., Óskarsdóttir, M. et al. Special issue on feature engineering editorial. Mach Learn 113, 3917–3928 (2024). https://doi.org/10.1007/s10994-021-06042-2

[3] Appermont, N. (2025). ‘A conceptual framework on legal complexity.’ The Theory and Practice of Legislation, 1–28. https://doi.org/10.1080/20508840.2025.2515804

[4] Tolochko, P., & Boomgaarden, H. G. (2019). Determining political text complexity: Conceptualizations, measurements, and application. International Journal of Communication, 13, 21.

 

Supervisor: Paul-Julius Hillmann

 

 

Topic 5: Enhancing Human-AI Co-Creativity: Investigating Generative AI Tools as Creative Collaborators (Master)
 
Description: The rise of generative AI tools, such as ChatGPT, DALL·E, and MidJourney, has opened new frontiers in collaborative creativity, where AI systems contribute to human creative processes. This thesis investigates the evolving role of generative AI as a creative partner – more than a tool, less than a human collaborator. GenAI tools can support ideation, problem-solving, and refinement across various creative domains. The study can take different directions, from systematically analyzing and structuring the “creative competencies” of generative AI tools to studying how users collaborate with generative AI in real-world creative tasks. Through surveys, user studies, and evaluations of creative outputs, this research aims to uncover human-AI co-creativity’s mechanisms, challenges, and opportunities. The findings will provide a deeper understanding of how AI can enhance creativity while highlighting potential barriers to effective collaboration.
 
Initial References:
 [1] Davis, N. (2013). Human-Computer Co-Creativity: Blending Human and Computational Creativity. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 9(6):9–12. Number: 6.
[2] Haase, J., & Pokutta, S. (2024). Human-AI Co-Creativity: Exploring Synergies Across Levels of Creative Collaboration (arXiv:2411.12527). arXiv. https://doi.org/10.48550/arXiv.2411.12527
[3] Heyman, J. L., Rick, S. R., Giacomelli, G., Wen, H., Laubacher, R., Taubenslag, N., ... & Malone, T. (2024, June). Supermind Ideator: How scaffolding Human-AI collaboration can increase creativity. In Proceedings of the ACM Collective Intelligence Conference (pp. 18-28).
[4] Hitsuwari, J., Ueda, Y., Yun, W., and Nomura, M. (2023). Does human–AI collaboration lead to more creative art? Aesthetic evaluation of human-made and AI-generated haiku poetry. Computers in Human Behavior, 139.
[5] Rafner, J., Beaty, R. E., Kaufman, J. C., Lubart, T., and Sherson, J. (2023). Creativity in the age of generative AI. Nature Human Behaviour, 7(11):18361838. Number: 11 Publisher: Nature Publishing Group.

Supervisor: Jennifer Haase
 
 
Topic 6: Exploring the Phenomenon of AI Companions and Virtual Girlfriends: Understanding Human Attachment to Digital Partners (Master)
 
Description: With the rise of AI-driven virtual companions and “AI girlfriends” in apps like Replika, a new dimension of human-computer interaction is emerging, blurring the lines between emotional connection and digital simulation. This thesis seeks to explore the psychological, social, and technological aspects of these AI companions. Key questions include: What motivates individuals to seek relationships with AI partners? How do users form attachments to non-human entities? What role does personalization and anthropomorphism play in fostering these connections? By employing web-searches, qualitative interviews, surveys, or case studies, this research will aim to uncover the broader implications of AI companions on social behavior, emotional well-being, and the evolving nature of human entanglement with genAI tools.
 
Initial References:
 
[1] Chaturvedi, R., Verma, S., Das, R., & Dwivedi, Y. K. (2023). Social companionship with artificial intelligence: Recent trends and future avenues. Technological Forecasting and Social Change, 193, 122634.https://doi.org/10.1016/j.techfore.2023.122634
[2] Dang, J., & Liu, L. (2023). Do lonely people seek robot companionship? A comparative examination of the Loneliness–Robot anthropomorphism link in the United States and China. Computers in Human Behavior, 141, 107637. https://doi.org/10.1016/j.chb.2022.107637
[3] Strohmann, T., Siemon, D., Khosrawi-Rad, B., & Robra-Bissantz, S. (2023). Toward a design theory for virtual companionship. Human–Computer Interaction, 38(3–4), 194–234.https://doi.org/10.1080/07370024.2022.2084620
 
Supervisor: Jennifer Haase
 
 

Topic 7: Extending XES and pm4py for Spatial-Aware Process Mining (Bachelor)

 

Description: With the growing maturity of IoT and sensor technologies, location data is increasingly available in real-world processes and digital twins. As this trend unfolds, the process mining community has also started to recognize the importance of spatial aspects, with emerging research often framed under the terms geo-aware, environment-aware, or location-aware process mining. While the XES standard allows storing location information as simple attributes, this approach can become restrictive for advanced spatial analyses. This thesis proposes an extension of the XES standard to represent location in a more structured way, alongside a pm4py extension for handling heterogeneous coordinate systems to enhance process mining capabilities with spatial awareness.

 

Initial References:

 

[1] Blank, P., Maurer, M., Siebenhofer, M., Rogge-Solti, A., & Schonig, S. (2016). Location-Aware Path Alignment in Process Mining. 2016 IEEE 20th International Enterprise Distributed Object Computing Workshop (EDOCW), 1–8. https://doi.org/10.1109/EDOCW.2016.7584367

[2] Corradini, F., Mozzoni, L., Piccioni, J., Re, B., Rossi, L., & Tiezzi, F. (2026). Modeling, Formalizing, and Animating Environment-Aware BPMN Collaborations. In A. Senderovich, C. Cabanillas, I. Vanderfeesten, & H. A. Reijers (Eds.), Business Process Management (pp. 106–125). Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-02867-9_8

[3] Fernandez-Llatas, C., Lizondo, A., Monton, E., Benedi, J.-M., & Traver, V. (2015). Process Mining Methodology for Health Process Tracking Using Real-Time Indoor Location Systems. Sensors, 15(12), 29821–29840. https://doi.org/10.3390/s151229769

 

Supervisor: Vito

 

 

Topic 8: Uncovering Business Process Structure through Variant Frequencies (Bachelor/Master Thesis)

 

Description: Business process variants typically follow a Pareto-like distribution: a small number of highly frequent variant accounts for most behavior, while a long tail of variants occurs only rarely [2]. Understanding such variant frequency distributions provides a rich source of insights into the structural characteristics of business processes.

This thesis empirically investigates variant frequency distributions of real-world and simulated processes. It aims to reveal underlying structural patterns and to test different hypotheses regarding their emergence. In doing so, the thesis contributes to our understanding of process structure and may also reveal insights into emergent process behavior.

 

Initial References:

 

[1] van der Aalst, W. M. P. 2016. Process Mining: Data Science in Action, (2nd ed.), Berlin, Heidelberg: Springer. (https://doi.org/10.1007/978-3-662-49851-4).

[2] van der Aalst, W. M. P., Bichler, M., and Heinzl, A. 2018. “Robotic Process Automation,” Business & Information Systems Engineering (60:4), pp. 269–272. (https://doi.org/10.1007/s12599-018-0542-4).

[3] Kabierski, M., Richter, M., and Weidlich, M. 2025. “Quantifying and Relating the Completeness and Diversity of Process Representations Using Species Estimation,” Information Systems (130), p. 102512. (https://doi.org/10.1016/j.is.2024.102512).

[4] Newman, M. 2005. “Power Laws, Pareto Distributions and Zipf’s Law,” Contemporary Physics (46:5), pp. 323–351. (https://doi.org/10.1080/00107510500052444).

 

Supervisor: Lennart Ebert